The Pittsburgh Supercomputing Center (PSC) has received a National Science Foundation (NSF) award to create a uniquely capable supercomputer designed to empower new research communities, bring desktop convenience to supercomputing, expand campus access and help researchers needing to tackle vast data to work more intuitively. Called Bridges, the new supercomputer will consist of three tiered, memory-intensive resources to serve a wide variety of scientists, including those new to supercomputing and without specialized programming skills.

Bridges will offer new computational capabilities to researchers working in diverse, data-intensive fields such as genomics, the social sciences and the humanities. A $9.65-million NSF grant will fund the acquisition, to begin in October 2015, with a target production date of January 2016. The system will be architected and delivered by HP® and will feature advanced technology from Intel® and NVIDIA®.

“The name Bridges stems from three computational needs the system will fill for the research community,” says Nick Nystrom, PSC director of strategic applications and principal investigator in the project. “Foremost, Bridges will bring supercomputing to nontraditional users and research communities. Second, its data-intensive architecture will allow high-performance computing to be applied effectively to big data. Third, it will bridge supercomputing to university campuses to ease access and provide burst capability.”

“Bridges represents a new approach to supercomputing that helps keep PSC and Carnegie Mellon University at the forefront of high-performance computing,” says Subra Suresh, president, Carnegie Mellon University. “It will help researchers tackle and master the new emphasis on data that is now driving many fields.”

“The ease of use planned for Bridges promises to be a game-changer,” says Patrick D. Gallagher, chancellor, University of Pittsburgh. “Among many other applications, we look forward to it helping biomedical scientists here at Pitt and at other universities unravel and understand the vast volume of genomic data currently being generated.”